University of Chicago - Master of Science in Financial Mathematics

University of Chicago - Master of Science in Financial Mathematics

Finding a full time job will be much more dependent on individual skills and efforts.
I graduated from UChicago FinMath in December 2022 and will be joining as a quant strategist at a Chicago prop shop.

Career Development Office
As mentioned in the previous reviews, Emily is an amazing career advisor. Not only does she give excellent interview and career advice, she also provides the moral support that is needed during the recruitment process.

Course reviews:
There are some courses in the program that I believe are worth taking:
- Portfolio Theory and Risk Management I
- Options theory/Numerical Methods
- Stochastic Calculus
- Regression Analysis and Quantitative Trading Strategies. This course does have mixed reviews but I personally enjoyed it. It gives you an insight on how to manipulate data and simulate simple trading strategies.

For Seb's programming courses, I believe that they are good if you do not have a CS background. If you do, this course is should be more of a review and grinding Leetcode/Hackerrank will be more helpful (which is pretty much the homeworks anyways).

The program also gives you the opportunity to take courses from other departments. Students should leverage this and take courses such as probability and statistics and machine learning courses from other faculties. I also highly recommend that you take a course from Chicago Booth; some of the courses there are very well taught.

Project Lab
Project lab is a nice touch to the program. It allows students to work with industry employers on a quant project. This experience can be used as a resume boost and be talked about during interviews. Students can also get internships and full time roles from this as well.

Overall, I had an amazing time in the program and will really cherish my 15 months there. I would take the Quantnet 2023 rankings with a grain of salt and do your own research into all the Master's programs. At the end of the day, making it to any of the top programs is impressive and finding a full time job will be much more dependent on individual skills and efforts. Hope this review helps!
Yes, I would recommend this program to a friend
Students Quality
5.00 star(s)
5.00 star(s)
Career Services
5.00 star(s)
I am December 2019 graduate from University of Chicago’s Financial Mathematics (MSFM) program. This program has transformed me and helped me achieve my goal of breaking in the [quantitative] finance industry and has given me the tools I need to succeed in the workplace. I want to thank all the faculty, students and other professionals I have worked or networked with along the way. For that, I cannot give the program anything but 5 stars for a rating. Although there are areas that need improvement, if you utilize your resources wisely, you will succeed in the program and ultimately start (or continue) a successful career path. This is an extensive review meant for prospective students to consider when choosing a program and also for current students on what they should look out for when attending. Feel free to reach out if you have questions on my review or on the program.

US Citizen; white male; BS Mathematics from a state school in NY (SUNY); 1 year of full time experience as a pricing analyst for an engineering company. Even though I had a limited finance background, the pricing analyst job was important in the sense that I got comfortable analyzing data via Excel but also being able to communicate esoteric analytics to stakeholders and clients. A big reason why I got admitted, despite the non-financial background, is because of the interest and willingness to undertake quant-related projects and learning how to code before starting the program. Moreover, I took several actuarial science courses, albeit unrelated, that showed my interest and ability in applied math.

Did you get admitted to other programs?
I got into a few programs but my next best option would have been Columbia: Mathematics in Finance (MAFN). It was a difficult decision for me but ultimately I chose Chicago and it ended up being the right decision. At the time, Columbia was much less transparent and had difficulty communicating with me and answering my questions via E-mail or phone (even after I had been accepted). On the other hand, Meredith Muir (Assistant Director for Student and Faculty Services for the program) was very extremely helpful with any concerns or questions I had. To me the program seemed more intimate in the sense that it felt more like a community. Columbia was also more expensive. There were a few other programs I got accepted to but turned them down.

Why did you choose this program (over others, if applicable)?
See above answer. To add on, I would say that UChicago has a great reputation and brand and this holds true even for masters or PhD programs. Granted, the undergraduate ranking has the true “elite” reputation but the prominence is still applicable to higher education. Even though the feeling eventually fades, stepping on UChicago’s campus and being surrounded by its architectural beauty, is a humbling experience. Industry heavyweights like Eugene Fama, Myron Scholes, Milton Freedman and other Nobel prize winners have been here to study, conduct research or teach. Lastly, growing up and having attended school in NY all my life, I was keen on moving out and expending all my energy on a new start in a new city (Chicago is definitely a fun city to spend ~1.5 years in).

Application process
Standard GRE/GPA evaluation along with an essay and video interview. The programs selection process is holistic in nature and they will give you a chance if you show them that you have interest and potential. You can find out more information through Meredith. I’m sure if you reached out to her she will answer any of your application related questions.

Course selection
The course selection I would say is relatively standard in the sense that the main toolkits you need in quant finance will be gained: option pricing, numerical methods, Python, C++, stochastic calculus, and portfolio management. The downside however is the lack of diverse electives. I was quite disappointed that the electives were either too specific (e.g. Multivariate Data Analysis via Matrix Decomposition) or too concentrated in one area (e.g. multiple courses on Market Microstructure or Algorithmic Trading). I understand that Chicago is a trading hub but not everyone who graduates from this program wants to be a trader. Moreover, the timing of these courses is somewhat inconvenient -- there were some electives I wanted to take in the Spring but I was too preoccupied by the required courses. Looking back, I would say the bulk of what I have taken from the program is from the required coursework.

Quality of teaching
Before I list out the faculty and their strengths and weaknesses, I want to emphasize that the core course professors are also involved in the management of the program and wear multiple hats (e.g. Roger Lee as the options pricing professor and the Director of the program, Mark Hendricks as the portfolio theory professor and Associate Director of the program, etc.). This means that you will spend more valuable time with these people outside the classroom and gain exposure in many different ways than just coursework (e.g. technical interview labs, clubs, career/employer events, etc.). I am going to give an in-depth review of the required courses professors and give a brief review of the other notable ones.

Roger Lee: FINM 33000 - Mathematical Foundations of Option Pricing. This course is the highlight of the program and the reason why you should attend this program. There is not a more qualified person to teach such an introductory, yet vital course such as this one. Put it this way - for my first project on the job post-graduation I had to read multiple research papers for the model I was working on at the bank and his name came up multiple times in the references section of these papers and even directly in the model my firm built. His teaching style is relatively slow paced but it is the reason why Roger is unlike anyone else. He takes his time to teach and makes sure everyone understands and explains extremely thoroughly. I don’t think there was ever a time he was unsure of what he was talking about. He’s a leading industry expert with many research publications. I still to this day, for my job, refer back to his notes and lecture videos. Roger also teaches FINM 32000 - Numerical Methods, which is a great course that has important topics. For some reason, I wasn’t able to get that much out of it at the time but now that I work more closely with some of the things he mentioned, I was able to go back to his notes and found it helpful. The homework’s are a combination of Python exercises and written examples. For both courses, Roger’s homework assignments are extremely well written, thought out, and useful.

Mark Hendricks: FINM 36700 - Portfolio Theory and Risk Management I. To start, Mark is a great guy - very personable and understanding. He is engaging in the classroom and is always willing to help. This class is of utter importance to anyone who wants to manage a portfolio or trade (even if this is not your job in the short-term, anyone in quant finance will eventually need to understand risk-return dynamics to either make money for a firm or for themselves). Aside from it being great course content-wise, I would like to add that Mark also served as our Coach for the McGill International Portfolio Challenge (another good way to get exposed to portfolio management in UChicago). He was there to guide us with our approach on the case study even though this was outside the bounds of the program - this is what I meant by saying that the professors wear multiple hats earlier.

Sebastian (“Seb”) Donadio: FINM 32500 - Computing for Finance in Python. I don’t think you can find a better programmer than this guy - he also teaches at Columbia for the Financial Engineering master’s program. Seb is an extremely interesting and funny guy who has many hobbies outside of finance which makes his course more fun to sit in on. Although Seb’s course gives you much opportunity to learn Python (“you will eat Python!”) with what seems like an unlimited amount of homework and exercises, to me it was a bit of a quantity over quality kind of class. You do get better at programming, but for a beginner like me at the time, it was tough to really grasp anything. For example, he would have multiple slides on commands found in the Pandas package (this is easily Google-able and people will always utilize StackOverflow for these while working when unsure), whereas the main important points of what DataFrames are used for, examples found in practice, and why it’s important to manipulate the data inside would be more valuable information. His written exams were a pain (although now his course has changed to HackerRank so you won’t have to deal with this). My Python skills progressed more in due time with other courses that came after this course and most quickly while working during my internship or full time. So, although it gives you a lot of time to go through exercises, for me the course kind of just passed me by and I haven’t used any of his course resources after the class (unlike Roger’s course materials which I use very frequently even after graduating).

Steven Lalley: Stochastic Calculus. Very smart guy but the course was extremely mathematical (Lalley is from the pure math department). For me, as a math undergrad, it was relatively interesting but a lot of people found it intimidating or just not useful. It was required at the time (now an elective) and most people had to pass fail this course. This course is a combination of theory and applications but felt more heavily geared toward theory which can be daunting and unrelated if you are not going for your PhD.

Yuri Balasanov, Lida Doloc, Jeff Greco: FINM 33601 - Fixed Income Derivatives. I, and others will probably tell you, that this course was pretty much a waste of time and money (to put it honestly and bluntly). The only semi-valuable thing gained from this course is the lecture notes which can probably even be found better written in other papers or online. The course was too disorganized and nobody seemed to know what’s going on in class or was really attentive to the material. The labs utilizing Bloomberg data and doing some calculations in Excel were just pointless. The homework assignments was re-used from previous years and had little practical application - a lot of formula derivations. There was one however useful discussion and homework exercise in Python on PCA - probably the only thing that really stood out to me in the class. This course has so much potential and to me it seemed like the program blew it. My recommendation for the program is to revamp this course by spending less time going over every little thing and spend more time on one vital and focused application for each lecture. For example, you can spend a whole lecture discussing how one specific exotic derivative is priced or replicated and then do a homework on building a pricer by running a Monte Carlo or PDE, test for errors and convergence rate, etc. -- things actually done in practice instead of just giving us all the formulas for floors, caplets, swaptions etc. (these things are easily found online). Then this idea can be carried over to other derivative products.

Niels Nygaard: FINM 33160 - Machine Learning. Fun Fact: Niels is the founder of the program. He is a very bright person and I found him to be helpful for questions related to HW or outside projects that are coding or ML related. The downside was that I found his class to be kind of monotonous as he would go through code line by line. Not sure how else to teach ML though but for what it was I can probably re-use the lecture notes or the actual code in the future.

Materials used in the program
I liked mbeven’s answer: “a computer and a brain” so I will go with that.

-McGill International Portfolio Challenge. I got a chance to travel with my fellow students to Canada to compete and numerous hours in the lab working on this outside of whatever I had going on in my courses. See MIPC website for more info.
-Project lab: I’m sure you have heard from others by now what this is so I will not describe it but I had to chance to work with a bank on a credit curve modeling project. I even traveled to NY to present to the team but most of the work was done remotely via biweekly phone conferences. It was an interesting and relevant project but was tough to grasp for me in the autumn quarter as I have not dealt with this material before but overall it was a good experience to get exposed and have on my resume. I would recommend if you are more experienced to take project lab after Autumn quarter so you do not get swamped with courses. If you have limited experience it will be better to take an autumn project lab to have something relevant to discuss for an internship superday (as was the case for me).

Career service
If I can give an MVP award to any person I met along this program it would be Emily Backe - Director of Career Development! (I would also give Meredith Muir one for being the life of the program). Emily and others (Alma Ceballos and Danny Michael) are there to guide you for any career advice you seek. This goes beyond just resume writing or interview tips. Emily was literally there for me when I had to make life-changing decisions - such as choosing or switching jobs). It’s really hard to find someone as committed, passionate and enthusiastic in their job as Emily. I highly recommend you utilize what Career Services has to offer - there is inherent value in this program just from the career services, especially if you had limited experience like me. There is a downside, however, associated with the career services -- see below section on
“Suggestions for the program to make it better”.

Student body
Everyone was very friendly and willing to help - I initially thought this was going to be a cutthroat program when I walked in but that was definitely not the case. We had multiple parties throughout the year completely outside the program to get to know each other or just enjoy our time in Chicago. Student life for me was important because I served as the Student Board President where my team and I organized many events our program sponsored to come together as what felt kind of like a family - Chinese New Year dumpling making event, Super Bowl party, ice-skating events, a few pub nights, and best of all: an all-inclusive booze cruise on Lake Michigan. The student body is not too diverse as the majority of students are Chinese natives but this is the case for most quant programs. There were a few other international students in my graduating class from places like Mexico, Spain, Canada, and Singapore.

What do you like about the program?
All the positive aspects mentioned in the above answers. The main point to get across is that the program helped me get a good job after graduating. Other pros include: Bloomberg terminals in the lab; taking the Time Series course by Ruey Tsay (he wrote the book on time series analysis) from the Booth School of Business; numerous behavioral/technical interview labs; getting a solid general finance background which motivated me to pursue some standardized finance certifications; the network you gain from meeting people in the industry or faculty; huge bonus is that all the lectures are recorded so if you miss or cannot attend you can watch online - I mentioned earlier that I re-watch Roger’s lectures when I need understanding in some options area for work.

Suggestions for the program to make it better
-See section on “Course selection” where I discuss electives.
-See feedback on “Quality of teaching” section where I discuss some cons of the coursework.
-Although Career Services is helpful by preparing your resume or prepping you on the behavioral component, the job listings they send you and the Career website resources available (FinMath Connect) post lackluster or outdated jobs. In that aspect, you’re expected to just apply to as many positions as possible. It would be much more helpful if they were more active on personalizing the experience for each student and helping students connect with more alumni or industry professionals to tap into a warmer network. And one more point on the career services - although I had lots of phone interviews, it was hard for me to close out some “superdays” and get an offer. I understand this is my responsibility but some more guidance or training on final rounds would have helped me.

What is your current job status?
Quant at a bank.
- Computer Science undergrad with a few years of work experience as a software engineer.
- Started working as a Trader after graduation in December 2022

Other Admits:
- UCLA and UC Berkley MFE
- Chose UChicago MSFM due to close proximity to many trading firms as well as lower overall cost.

Overall I believe the program has a mixed bag of experiences that bring my rating of the program to a 3.5/5. There are some truly exceptional portions to the program as well as a few downright terrible classes/professors that make you question if you're wasting your time and money.

- The program begins 2 months before the official start date. It begins with an August review that brings students to a base level of understanding required in the program. The program attracts students from a wide range of backgrounds and not everyone is fully equipped with the resources to delve into the material. The topics cover a wide range such as regression analysis, probability, programming etc. This time is both useful to brush up on material you may not have experience in as well as prepare you for the level of coursework once classes start.

September launch provides more classes as well as opportunities to meet other students and alumni. There are social gatherings to acquaint incoming students and also workshops and seminars to help you in your job search.

- The first quarter the probably the best part of the program. Roger Lee and Mark Hendricks are both phenomenal professors/lecturers and all three suggested classes (Portfolio Management, Options Pricing and Python) had a lot to teach. This three classes combined with the job search provided a very rewarding first quarter which left me with very high expectations with the rest of the program.

- The support staff are also extraordinary. Meredith and Emily are the two main callouts that come to mind. Meredith is always available for you to talk to, whether it is personal or professional. If there is anything that you need to have done, she is the go to person. Emily is likely the best career advisor I ever worked with/will work with. Saying that she goes above and beyond is honestly an understatement. I genuinely don't know how she was able to make the time to answer everyones questions. She makes sure to understand each student's unique situation and provides insightful guidance even when you yourself may be unsure on what you want/need.

- The program provides flexibility in what electives you want to take. You have the option to take classes from Booth and Stats departments within UChicago.

- All the classes (bar a few where professors forget) are recorded start to finish and uploaded online. This allows you to rewatch to see portions that you may have missed as well as play the video back at 2x speed to review.

- Being located in Chicago it's easier to meet/see many of the trading firms that are located there.

- There were a few months where Emily temporarily left the program. This along with a few other changes in the Career Development Office (CDO) were very noticeable. However, now that she's back, maybe things will be back to normal (though she's not in the same role).

- Too many classes that are not worth taking. Further details below.

- Chicago winters and crime

Courses to take: Modern Applied Optimization, Bayesian Stats I and II, Microstructure, Stocalc, Numerical Methods, Portfolio Theory, Option Pricing, Python

Classes to avoid:
- Regression Analysis and Quantitative Trading Strategies with Brian Boonstra: Overall this class taught me very little. It was largely a project class that are focussed on teaching you how to manipulate and display data. The "trading strategies" are incredibly basic and something that you could teach yourself by looking at wikipedia. Grading made no sense as they would often times give you an 80 with the only comment being "Great work". The lack of feedback gives you no opportunity to learn nor the willingness to try on future assignments. This class was likely the biggest disappointment I had in the program as the reviews made it seem like it would be a great class.

- Probability and Stochastic Processes with Jostein Paulsen: The material in this class was actually great, it was just taught very poorly. Partly due to the fact that there was too much material for a 50 credit course, partly due to bad a bad professor. This class could be very valuable if they rework it to be a 100 credit course with more depth.

- Applied Algorithmic Trading with Christopher Gersch: The homeworks were again graded completely arbitrarily with no feedback. The final project also had no feedback and seems to be graded based on entertainment value. It's not a difficult class, but just doesn't provide much educational value.

- Blockchains and Cryptoassets for Finance with Brian Boonstra and Co.: Material was not very informative and some of the homeworks seemed like they were designed for a middle school class.

- There are other classes that I heard bad things about through word of mouth, however since I didn't experience them personally, I won't comment on them.

Tips going in:

- Study the Green Book ("A Practical Guide To Quantitative Finance Interviews”), prior to the program if possible. As Emily and others will tell you, it is never too early to start interviewing.

- Keep track of places you're applying and apply far and wide. Keeping track of your applications during the internship process if very helpful when deciding where to apply come full time.
I graduated from UChicago's MSFM program in December 2022 and will work as a Quantitative Equity Trader in the emerging markets pod at a leading mutual fund.

My background was in Economics and Finance, and I had some experience in Quantitative Research. My goal from this master's program was to learn everything I could to become a better quant and discover the things I didn't know or was ignorant about in quantitative finance.

The quant net ranking has s strong bias towards programs in New York and the primary east coast cities. The ranking system unfairly makes UChicago seem like a weak choice when looking at schools. Take the rankings with a grain of salt. Judge each program based on the coursework they offer and the quality of the research the school and program do. By its very nature, the school and the MSFM program require you to be able to do the work and also to research why you want to do it. When I speak to many people in the industry, the program garners commanding respect from everyone because those who know, know. The expectations employers have from graduates of this program are sometimes overwhelming, due to the ecosystem the program has built, from the faculty, staff, and support staff whose goal is to see every one of their students succeed.

If you are looking for a program that spoon-feeds you or a quid pro quo relationship, my advice doesn't apply. This program is for people who are committed to working hard, questioning everything, and working with their cohort to solve problems.

As a quant, I need to back these statements up and show that this process is repeatable and does achieve the desired results. This result is entirely up to you and depends on how hard you work.

The three pillars of this program are its faculty, staff, and support staff.

Professor Roger Lee is one of the most sought-after people in understanding and building options and strategies for both exchanges and funds. His classes, which you will take in the Autumn and Winter Quarter (Options pricing and numerical methods), are enlightening. He has a way of conducting the classes that make you think and understand everything he teaches you. It is measured, every word is relevant, and if you listen to the zoom recording or read the transcript, it is uncanny how precise each word is and how it makes you understand the most complicated concepts in simple terms. When doing your interviews, the interviewers ask many questions related to options. If you understand both of Professor Lee's classes, you will make it to the final round.

Professor Mark Hendricks is another one of those professors who have this knack for distilling knowledge very eloquently. He teaches the Portfolio Theory class and the Corporate Credit and securities class. Even if you don't come from a finance background, you will get up to speed within the first few weeks. His course teaches the basics you need and then gets you to apply those basics to solving and figuring out real-world problems using case studies. He guides you through the thought process and embodies the philosophy of teaching "how to think," not "what to think." He is also one of the best resources in the program to ask for some guidance on interviews or a general chat. No matter how busy he is, he makes the time, which is the dedication you get from this program.

Finally, Python by Seb. You will know where the term "where fun goes to die" originates. These courses are intense but essential if you want to do technical roles in the industry.

The other courses I recommend are from the Math or Stat department. Take advantage of the fact that it is one of the world's best math and stat departments. The professors are simply exceptional. I was fortunate enough to take a Multivariate Statistical Analysis class taught by Professor Mei Wang. This class was one of the best classes I took at UChicago; she taught me all the necessary statistical methods and tools.

The program, from the get-go, starts helping you with your search for an internship. Emily Backe, the program's chief of staff and previously the director of the career development office (CDO), was instrumental in helping me get my internship and a full-time job offer. The CDO provides resume reviews and technical and behavioral workshops, and they act like a sounding board for all the frustration one goes through during the recruiting process.

The special glue or "X-factor" that makes this one of the best programs in the world is the support system we have which is taken care of by Meredith. She is the one who knows everything or will guide you to the right person who can help you. She helps navigate all the logistics of getting your visa, guides you through the program, and advises on what courses to take. She helps organize our classes and events and is an excellent sounding board for all related and not related to the program.

The program was one of the best decisions I have ever made. It was tough and not to mention frustrating at times. The friends you make here will last a lifetime and help you in almost anything; in essence, you gain a family. The city of Chicago is very vibrant and also helps in being very accommodating to students. If you love to learn and put in the effort and hard work, this program is for you. Coming out of the program and looking back, you will see how far you have come and how well this program prepared you to tackle all the challenges you will face, personal or professional.
One of the best decisions I have ever made in my life.
I recently graduated from The University of Chicago's Financial Mathematics Program in December 2022. I will work as a quantitative analyst of a top custodian bank in US.

My Background
Previously I worked six years as an economist and strategist for a leading financial institution in Asia. My motivation ,target and goal is to learn most top-notch quantitative skills from math to programming to utilize extensive datasets and to provide more convincing investment ideas.

Career Development Office(CDO)
Emily is the most professional, committed, compassionate, enthusiastic, kind, nice, sweetest and the most responsive and the most supportive and the most helpful professional in this program. She CARES student and knows all the answer to the career questions that graduates had. Without her help and support, I would never be able to secure the job offer.

During the interview process, Emily followed up with my job hunting and provided professional and instant response. What Emily offered is the industry standard. Emily provides insightful guidance and customized advice based on different personal background. Regarding to career path choices, there is a lot to consider. Emily will discuss with you all the opportunities and let you know the possible outcome. Emily is there for me when I had to make life-changing decisions.

Career Development Office provides world-class career service and helps with resume writing, LinkedIn updating, Technical Interview Seminar and Mock Behavioral interview Lab.

Student Service
Meredith is always there for students to talk to and share everything from visa consultation, course selection, course registration process, to accommodation for exams. She is extremely helpful with any concern or question that I had.

Meredith organized our events and classes from architectural boat tour to painting class. She is extremely involved with our cohort. The University of Chicago's Financial Mathematics Program seemed more intimate because our cohort felt more like a community.

Course recommendations
There is more to come. You will have the flexibility to choose fixed income and time series courses from the Booth and math & stat courses from both department.

Roger Lee : Mathematical Foundations of Option Pricing/Numerical methods
Professor Roger is not only smart but he also makes sure every student understand the materials. Roger had a magic and a great way of getting everyone understand the hard Math concepts.
What Roger teaches is not only the theory and but also the real world application of it. Roger will go over brain teasers and interview questions that students have seen during interviews at top firms.

Mark Hendricks : Portfolio Theory and Risk Management I
Professor Mark CARES students and is extremely dedicated to his course. Mark designed the homework rigorously and guided students to figure out the thought process. Mark combines python programming applications of portfolio theory using Harvard Business Case study approach in homework and for discussions. That really helps students to understand the real-life applications and essence of quant portfolio theory.

Professor Mark will also prepare statistical interview questions from time series, regression to financial markets analysis like fixed income. Based on my interview experience with banks and funds, most of the questions had been discussed thoroughly in the class and in the seminar/workshop.

Gregory Lawler : Stochastic Calculus
Professor Lawler is the best and the most respected mathematician contemporarily and the pioneer in the stochastic field such as probability and random processes. His lecture is easy to understand and his course is fun and interesting.

Chanaka Liyanaarachchi : High Performance Computing
HPC is the most useful programming course that I took in The University of Chicago's Financial Mathematics Program. Professor Chanaka will dive into various applications from OpenMP to CUDA. We will have the opportunities to have exposure to modern technologies.

Jon Frye : Portfolio Credit Risk: Modeling and Estimation
Professor Jon is the economist and risk specialist from Chicago FED. The lecture that Professor Jon taught in class is industry standard from PD/LGD to vasicek credit risk model. The homework that Professor Jon gave is to ensure students understand the risk management inside and out.

Project Lab
The project lab that I did with my cohort did help me secure the job. We will be able to be in touch with the current developments in finance through their relationships with practitioners.

I had true friendship for life when I was in the University of Chicago. I would say that they were my family. Most students are very friendly and willing to help.

The University of Chicago's Financial Mathematics Program
The program has a great team of dedicated professors, career and academic counselors, classmates and students. Its reputation in the quantitative finance industry will open doors for you and you will realize how much you have learned and grown during the 16 months. I would describe this program as the most challenging and most rewarding academic endeavor of my life, and would recommend it to anyone with a passion for learning more about the quant side of finance.

Two roads diverged in a wood, and I took the one less traveled by, and that has made all the difference.

The University of Chicago's Financial Mathematics Program changed my life. This is one of the best decisions I have ever made in my life.
Yes, I would recommend this program to a friend
Students Quality
5.00 star(s)
5.00 star(s)
Career Services
5.00 star(s)
You get what you want. Chicago winter is brr
I graduated from the UChicago Fin-Math program in 2022 Dec and I am starting my full-time quant trading role at a market-making firm in Chicago in 2023 Feb.

My background:

Undergrad -- Finance & Data Science major with a math minor
Full-time experience -- one year at a wealth management firm

What I liked about the program:

1. Location
- I finished my 4-year undergrad program in NYC and figured that NYC was not for me. I wanted a better blend of a big city but also having some nature / peace and quiet. Since I wanted to become a quant trader, Chicago seemed like the ideal choice being the trading / market-making industry hub, but also having the peace and quiet that I wanted. Its proximity to job opportunities also allows easy networking / coffee chatting.
- The city's architecture is also very nice. There are also a lot of museums that are definitely worth going to.
- The city's rent is much lower than other major cities. (Almost half of NYC's.)
2. UChicago's positive academic reputation
- The school overall is known for its academic rigor, reputable professors, and beautiful campus. With the Fin-Math program, you get access to not just the top-tier Fin-Math courses and professors, but also resources from other programs such as the Booth Business school, the stats program, UChicago Law School, etc..
- Some Fin-Math professors (namely Roger Lee, Mark Hendricks, Seb, and Greg Lawler) are amazing lecturers and have classes that have an amazing blend of theory + practicality.
- There are also out-of-Fin-Math professors (namely Mei Wang in the Stats department) who also teach very good classes.
- There are tons of research opportunities
- There are some times free / discounted social activities (show tickets, Michelin restaurant meals, skiing, etc.) that are posted by the school that's kinda neat.
3. The Fin-Math program's resources
I categorize this program's resources by its (1) courses, (2) career development, (3) other general / life resouces.
(1) courses:
- All of the classes taught by the professors listed above are highly recommended, plus the other recommended classes in other reviews.
- You also get access to non-Fin-Math classes like those in Booth, the stats department, and even the law school for Fin-Math credits.
***But since class schedules / professors may change every quarter, it's better to ask Meredith & alumni what classes to take (or avoid..) when the time comes.
(2) career development:
- Emily Backe in Fin-Math's career development office (CDO) is extremely resourceful, kind, and responsible. She can not only give you the perfect interview prep but also lead you to just the right people you need to speak to for your job search, interview prep, etc..
- Other professors (Roger, Mark, and Seb) will also help you with technical interviews. Their interview prep sessions are extremely useful.
- There are also industry professionals (called IPO) helping you with further interview prep.
- The program is designed in a way such that you get to meet students from a class above you during your first quarter at the program. This makes sure you have students to talk to who can tell you about their school + work experiences, and
(3) other general / life resources
- Meredith is the go-to for all your questions. She is fun, resourceful, and knows EVERYTHING about the program and its people. She will give you her most honest opinion (and all the intel she gathered from all the profs & students) on what classes to take or avoid. She will also lead you to any help you may need since she knows everyone... quite literally.
- The class size is fairly large (~100 people per class), which mean there's a larger variety of students from different background, etc. Students are all very nice here -- you can definitly make life-time friends from the program. Also, many students are very knowledgeable and have many years of work experience -- you can always learn a lot from your classmates.

What I didn't like about the program:

1. City's infrastructure & weather
- Many parts of the city, including but not limited to public transportation, road design, how people don't know how to drive, bad DMV systems, etc. are designed poorly and are extremely inefficient (and sometimes have bad service)
- Too cold.. brrr
- High crime rate (esp around school, aka the Hyde Park area)... However, you do have to be careful everywhere (plus most American major cities do have issues with high crime rates, although not necessarily as bad as Chicago's hyde park area..) Just be vigilant and try not to walk around alone in dangerous neighborhoods, especially when it's dark.
2. Career development office's flaw(?)
- For a while during my time in the program, Emily Backe was gone and the program's CDO was near non-existent with very insufficient support. It's awesome that Emily came back but the program's CDO is very Emily-dependent. Hope CDO hires more reliable staff soon so Emily doesn't need to be overworked...
3. Some classes were poorly taught and were a waste of money & time
- These classes are
4. Minor things that don't necessarily concern others
- Fin-Math's graduation for my year was meh ... The merchandise we got included a bag that has very low quality (had 2 holes already after using it once)
- The winter can be depressing with the school almost empty (most students take online classes in the winter). But it get's better in the spring & fall.


- I wanted to give 3.5/5 but QuantNet doesn't let me. Since Emily's back, I'll round it up to a 4/5.
- I didn't give it a 5/5 mainly because of (1) the bad courses that the program offers and (2) the inconveniences caused by the city's bad design / insfrastructure. However, I still gave it a score higher than 3/5 because you still can get what you want from the program.
Yes, I would recommend this program to a friend
Students Quality
5.00 star(s)
4.00 star(s)
Career Services
4.00 star(s)
  • Anonymous
  • 5.00 star(s)
Graduated from UChicago MSFM in December 2022. Started working as VP in Quant Research role at one of the largest banks.

Engineering from top Indian institution + 10 years’ work experience at Banks in Financial Markets/Derivatives Structuring + CFA

Other Admits:
UCLA MFE, Georgia Tech QCF
Choose UChicago MSFM because of the University reputation and the impressive communication with the program staff during my application process.

My top takeaways from the UChicago MSFM Experience:
1. Career Development Office – UChicago probably has one of the best Career Development Office (CDO) amongst all Quant Finance programs. Emily Backe was leading the CDO till last year and she is the Chief of Staff for the program now. She is simply superb at managing student career aspirations and has institutionalized multiple professional development tools. CDO helps with all career needs like resume building, LinkedIn profile updating, mock technical and behavioral interviews, networking opportunities, relevant job posting feeds and a lot more. You get personalized attention and can speak with Career advisors and alumni from the industry at any time. I personally kept meeting my career advisor multiple times during my summer internship search and she connected me with many of the program’s alumni from the industry.
2. Core Course Curriculum: The curriculum is structured to get you fully prepared for summer internship interviews right from the beginning of the program. Before the official start in the fall quarter, there is a month-long Review on Regression, Python, Probability and Stochastic processes. This helps you navigate for your interviews and continues seamlessly into more advanced course works in Option Pricing, Portfolio Theory, Quant Trading Strategies, and much more during the program.
3. Faculty: The core faculty of Roger Lee (Director and Instructor for Option pricing and Numerical Methods), Mark Hendricks (Instructor for Portfolio Theory and Fixed Income), Seb (Instructor for Python and C++) are all veterans in their domains and cover the topics like none other. There are newer electives in Bayesian Machine Learning and Crypto Assets taken by some industry professionals who are best in their fields.
4. Support System: MSFM is extremely intense where you are expected to learn and perform every day. The coursework becomes challenging quite quickly and you are also required to engage in summer/full time job search. But during my coursework, I never felt stressed out or broken down because of the cohesive environment at institute. Meredith, Director of Academic Services and Administration plays such a huge role in this by helping you at every step. She would advice you on any matter, personal or professional and helps you choose courses according to your aspirations and capabilities.
5. Concentrations and Ability to Tailor what you get from the program : There are multiple opportunities to tailor your course work as per your career aspirations. You can choose your courses to get a concentration in any of (1) Data Science, (2) Trading, (3) Derivatives and (4) Computing. Each of the concentrations have some courses that are taught by well-known industry professionals.

On the whole, the program is fantastic, and everyone takes away so much from it. I personalized gained everything I was looking for – A great career path, a wide and diverse professional network and above all, an excellent learning experience that would go with me for life.
  • Anonymous
  • 5.00 star(s)
I graduated from UChicago's MSFM program in December 2022 and will be working as a Credit Risk Modeller with one of the top bulge bracket banks in the USA.

My background was in engineering from a top-tier institute in India and I had some work experience in risk management. My goal with the master's was to shift to a more technical role and the program helped me immensely in this endeavor.

In spite of the lower quant net ranking, the U Chicago MSFM program has a few key advantages over most of the MFE programs being offered by other universities. We have one of the best career offices (CDO) out of any university and they help you start applying for internships the minute you accept the offer. The previous director of CDO, Emily is a superhuman and one of the best in the industry, currently, she is the Chief of Staff. CDO provides resume reviews, technical and behavioral workshops and they act like a sounding board for all the frustration that one goes through during the recruiting process. The amount of in-person events with companies in Chicagoland has also increased since Covid.

Academically, the program is rigorous and there is a lot to learn but it is never overwhelming, MSFM allows you to mold your experience according to what you need. The professors are industry-focused and are very patient with students.

Some of my recommendations are:
- Courses by Professor Lee (Option pricing and numerical methods). Professor Lee is the director of the program and his courses are super useful in interviews. He makes sure to cover all the required mathematical principles without making it seem overwhelming. It is critical that you take Professor Lee's courses if you want the full experience.
- Bayesian Inference and Machine Learning I and II from Gordon Ritter. Professor Ritter is one of the best quants in the industry and he has a very unique and insightful way of approaching problems, these courses are a must.
- Python and C++ by Seb. You will know where the term "where fun comes to die" originates from. These courses are intense but absolutely essential if you want to do technical roles in the industry. They helped someone like me with almost no programming background secure a very technical job.
- A course from the math/stat department. UChicago has one of the best Math departments in the world and while rigorous, the courses are great for getting your fundamentals right. One of the best ones for quant finance is the Stochastic Calculus course by the man who literally wrote the textbook for it - Professor Lawler.

- Courses to avoid: Any course by Prof Nygaard.

The program has a great support system too, Meredith takes care of everything and can solve any problem you throw at her, administrative or personal. She personally helped me navigate all the visa complications an international student has to face

Overall, I would say the program is fantastic if you want to delve deep into the world of quantitative finance. You'll have one of the best career offices in the country and the technical and soft skills you'll pick up will help you shape your career according to what you want. It helps that the university is based in one of the best cities in America.
I graduated from the program in December 2022 and will be joining a mid/large size prop trading shop in Chicago as a quant trader. Looking back to the 15-month journey in Chicago, I found UChicago did a tremendous job in helping me build my career path and explore job opportunities in quant finance industry. Here are some highlights:

Students in the program come from various background. The onboarding process and started 2 months prior to the official start date in order to get everyone to the same page.
This experience helps the most for those who have less experience or knowledge about the industry to get ready early for the short and competitive recruiting season.

Career Office
The career office is the strongest support for students’ recruiting. It’s very impressive when you realize there are only 3-5 people supporting over 100 students with their job search, organizing various career events, always replying to everyone’s email promptly while thoroughly, providing personal counseling any time one needs and continuously updating individualized recruiting strategy.
The support and resources I received from this group of people is invaluable.

Project lab
For those who had limited work experience, this is your best chance to get industry experience on your resume. For those who have had experience, this is a good chance for you to work on some solid projects that industry values or even an official offer.
Like everyone else on this review section, project lab added a lot to my experience. To make it simple, comparing the numbers of interview I received before and after I have a project lab experience, it is obvious to see its value.

In addition to the program itself, location is what I considered the best factor for choosing your school, but the decision criterion might differ for everyone.
Chicago being the biggest hub for prop trading firms in the world has the natural competitive advantage for you to break into the industry. As someone who aimed to get into prop at the beginning of the program, this is absolutely helpful. Not only for job search, but also after you join the industry, you’ll be surprised about how many UChicago alumni you will meet during work from your company, your counter parties, and your brokers.
Crime rate, weather etc. being the negative factors for the location do not bother me the most. I do envy the nice sunshine on a winter day on the west coast, but I guess that’s why have breaks and vacations.

Hope this can help you make the right choice.
Graduated in December 2022, working as desk strat at a major bank.

CDO: really on top and provides great connections with employers and alumni.

Curriculum: provides almost all aspect of quant finance knowledge from pricing, computing to economics. Also the teaching staffs are a gold mine. Once you reach out they offer bottomless help.

The program really is a buffet. You can get what you want and all you need to do is to show up and grab a plate.
I graduated from UChicago MSFM last December, and I am set to work as a quantitative researcher at a bank in NY. Overall I am extremely satisfied with the program.

Hard science undergrad. Several years of experience in finance in Asia. Hope my review is particularly helpful for prospective students who are already experienced in some way, as this was my case.

Why I chose this program?
I was admitted to several programs mentioned in quantnet. I reviewed the course lists of each program. UChicago MSFM had a good mix of theory and domain-knowledge courses, and the course choice was flexible. I knew what courses I wanted to take and not, so this was a big plus. If you were in my shoes, you probably would want to take courses that you need instead of a course in which you're going to get an A. So I encourage you to review the course lists. Also, the program allowed students to take courses from other departments, mainly statistics and Booth. I highly benefitted from this flexibility.
Of the programs I was admitted to, MSFM was the only program that offered project lab each quarter. I participated in the project lab in nearly all quarters and was able to gain insight and connection. It was a big differentiator for me because when I graduate, I'd need to work full-time to get a taste of a business I'm interested in (which is a big commitment).

Course reviews:
Roger Lee: taught option theory and pricing methods. Anything Roger teaches, I highly recommend you take because he is amazing. He can explain complicated concepts in a crystal clear way. Initially, I was not enthusiastic about his options class because I thought I was already familiar with the materials. But I did not regret taking his course. He cleared out all of my bogus mathematics and replaced my complicated solutions with simple solutions. I glimpsed at some of his research papers. Even though I cannot produce this quality research, I could still appreciate his amazing ideas (if you are interested in the topic, you don't need to for exams). What some financial mathematics professors prove with long long lines of hard algebra, Roger, with his brilliant ideas, can prove in much fewer lines.

Mark Hendricks: taught portfolio theory and credit. Mark is a very good teacher and a nice pleasant person. He really cares about students and would go out of his way when you have something to discuss. He emphasizes explaining in words our understanding, which is what you need to do in interviews.

Seb Donadio: taught Python and C++. Seb is probably going to be your memorable professor. One of the most intense courses for me. Even though I was familiar with the languages, I spent a lot of time on assignments and projects. Instructions need some work because they can be vague and confusing, but I encourage people to take his courses to get the full experience of MSFM. The strength of his courses is the domain knowledge he shares. He is a highly experienced professional and doesn't mind sharing what he knows. I appreciate that I learned not only more about the languages but also how they are used in the financial industry. I found his courses very helpful in interviews.

Gregory Lawler: taught stochastic calculus. He is a distinguished scholar and a very good teacher - a must-take for quant finance wannabes.

These are the courses nearly everyone takes, and you can choose the rest of the courses from both the Financial Mathematics department and other departments. You don't want to stack up too much in the Fall quarter due to recruiting. Other quarters can be as hard as you want them. Generally, I am happy with nearly all the courses I've taken.

One of my favorites in the program. Emily Backe was a world-class career consultant (no longer part of CDO anymore, promoted for the better good of the program - but she is still here). She is extremely caring and knowledgeable. The CDO had ample industry knowledge that helped me navigate my way. They did not provide just generic career advice.

I am extremely happy with the knowledge I gained in the program and the career outcome. I'll stay in touch with people I met in the program. Not really understanding why UChicago's ranking is so low on the quantnet ranking table, though I cannot speak of other programs I didn't attend. But in my personal opinion, the ranking is irrelevant to individual success (as a potential quant finance wannabe, you shouldn't take information as is anyway). I hope the prospective students find a program that suits them most. Wish you success.
Evening classes available!
The cohort consists of a healthy mix of young graduates and more mature students with experience in the industry. This diversity is reflected throughout my experience at the program. Students have prior background in financial mathematics are also allowed to take a certain number of electives from other departments (e.g. the renowned economics program or business school). The new track system allows students to build a more tailored curriculum and focus on areas that they're most interested.
Yes, I would recommend this program to a friend
Students Quality
5.00 star(s)
5.00 star(s)
Career Services
4.00 star(s)
Can you tell us a bit about your background?
B.S. Engineering Physics (High Honors), University of Illinois at Urbana-Champaign, 2002
B.S. Computer Science (Highest Honors), University of Illinois at Urbana-Champaign, 2002
Five years of IT and software development
I studied full-time in the program from 9/2007-6/2008

Did you get admitted to other programs?
Yes; NYC Courant's Mathematics in Finance and Carnegie Mellon's MS Computational Finance
Why did you choose this program (over others, if applicable)?
Short duration, lower cost of program and of living, reputed heavy mathematical focus.

Tell us about the application process at this program
Online application. Had to submit GRE General test scores. Went smoothly.

Does this program have refresher courses for incoming students? How useful was it?
There were free courses offered to incoming students which were nominally "refresher" courses. In practice, these courses were survey courses in material that students were unlikely to have been exposed to. Several of them were very useful; the measure theory course conducted by Robert Fefferman was outstanding, and the finance introduction by Tim Weithers was well-done.

Tell us about the courses selection in this program. Any special courses you like?
Mathematical Foundations of Option Pricing - excellent
Numerical Methods - excellent
Statistical Risk Management
Stochastic Calculus
Data Analysis And Statistics - disastrously bad
Topics in Economics - well-taught, but questionably relevant
Portfolio Theory and Risk Management - good
Foreign Exchange
Fixed Income Derivatives - wildly mixed quality depending on presenter
Advanced Option Pricing
C# Programming (optional)

Tell us about the quality of teaching
Teaching quality ranged from very competent to insultingly poor.

On the "competent" end, Roger Lee deserves particular commendation for his course preparation and delivery in Mathematical Foundations of Option Pricing and Numerical Methods. The design and delivery of both courses was absolutely meticulous and well thought-out. Other instructors who deserve positive mention include: Paul Staneski and John Zerolis (Portfolio Theory), Lida Doloc (Fixed Income Derivatives), and Jostein Paulsen (Stochastic Calculus, Statistical Risk Management).

Sadly, there were also several instructors who did not appear to feel it necessary to assemble a coherent syllabus or present their material in an understandable fashion to the students in their classes. Chief among these was Per Mykland, who "taught" the Data Analysis and Statistics course (and I believe in most years teaches stochastic calculus as well). His lectures were very rough surveys of material which was inaccessible and unknown to most of the students in the course. Generally, no supplementary reference texts were mentioned to provide comprehensible explanations of the topics covered, and his lecture notes were filled with errors that had clearly gone uncorrected for years. Much of the final section of his notes consisted of text copied directly (save an occasional misspelling) from N.H. Chan's _Time Series_. The material covered by the homeworks was often not addressed by the lectures; in fact, the head teaching assistant informed us in no uncertain terms that he expected most of the class to fail the second homework. The teaching assistants were often unable to help with the homeworks, leading me to believe that they frequently did not understand the material any better than we. Students did so poorly in the class that he announced his intention in the final lecture to simply give all students 'A's in lieu of a final exam (though he was later overruled).

Professor Mykland's disregard for his teaching obligations is legendary; there are discussions on Wilmott Forums of his lack of concern for his audience's comprehension all the way back in 2005 and it seems that little has changed. Unfortunately, data analysis and statistics are fundamental to financial mathematics, and for those of us who did not enter with graduate degrees in statistics, we were left woefully unprepared for the remainder of the courses (particularly stochastic calculus and statistical risk management) as well as job interviews. As a particularly pointed example, I was unclear on what a "standard error" was until I engaged in a program of self-study after his which I got an A-.

Materials used in the program
Primary texts included:
- Hull's _Options, Futures, and Other Derivatives_
- Carmona's _Statistical Analysis of Financial Data in S-Plus_
- Ingersoll's _Theory of Financial Decision Making_
- Bjork's _Arbitrage Theory in Continuous Time_

I also found Baxter and Rennie's _Financial Calculus_ to be an excellent introductory text, though it was not used directly in the courses.

Programming component of the program
Excel, R for statistical analysis, MATLAB for numerical methods, C++ with Quantlib for some interest-rate derivatives work. The introductory programming courses were taught in C# and covered basic ASP.NET. Many of the homework assignments had a programming component.

There were few "projects" per se, though much of the homework was group work.
Career service
Unknown; I didn't use them.

Can you comment on the social interaction between students of different ethnics, nationalities in the program?
Many of the Chinese students formed a fairly tight social group, I suspect due to shared language. The remainder of the students were very outgoing and mingled and worked together freely.
What do you like about the program?
Excellent instruction in a few topics, a good reading list, U of Chicago name on the diploma, meeting a lot of great people.

What DON’T you like about the program?
The general disregard for the quality of education received by the students.
Suggestions for the program to make it better
- Dismiss Per Mykland.
- Solicit feedback from students to ensure that professors generally are doing a good job, and reward them or remove them accordingly.
- Ensure that professors are aware of how their courses fit into the overall curriculum. Many of them seemed unaware of what students entering their classes would and would not be expected to know.

What are your current job status? What are you looking for?
I am employed by an investment bank as a software developer, and would like to find more quantitative challenges in the near future.

Other comments
If you have a graduate level of statistical experience, are very comfortable with PDEs (and preferably SDEs), and are willing to put up with having to fight to learn in some classes, you could get a lot out of this program. Otherwise, I would suggest going elsewhere.
Not bad and sounds like things have been improved

What do you think is unique about this program?
Hard to say because I only have second hand info about other programs, but I will try:

I felt like the pace was really fast. When courses drag on too long, it's easy to lose interest and motivation.

Also, there were some really good professors: Paulsen was an excellent lecturer and was very helpful in understanding the material. Lee did real well at explaining and teaching some pretty complex and deep material (for me). Hanson did a great job making stochastic calculus accessible to someone with an engineering background. Even though Fefferman only did a few days of intro on measure theory, he was also excellent at making very theoretical and deep material accesible. There is no shortage of teaching talent, but not every professor is awesome.

What are the weakest points about this program?
The year I went (2009-2010), there were way too many students admitted (~150, which means around 250 people in lecture, including part-timers from previous years). About half seemed legit and about half seemed like undergrads who couldn't get jobs and whose parents had the money to send them. Essentially spoiled brats with no manners. They made it difficult for the instructors because they don't shutup for lecture and they were always suspect of cheating, so the instructors had to be jackasses during exams and during lecture a lot of times. Some of these kids were really bright and some, well, were just kids with no professional experience and no clue how to conduct themselves. Of course, I believe this has changed and the year I went was definitely a transitional period for the program.

This is a minor complaint, but I think there could have been a little more flexibility in the curriculum. For instance, I would've liked to take some computer science classes like machine learning or AI. and perhaps some accounting or more pragmatic finance courses in the business school. It would have rounded things out well if I could've done that.

Career services
I tend to think, "You make your own breaks," for stuff like this. There were quite a few companies recruiting and there were opportunities, just not as many as a b-school student would have. But then, b-school grads get hired into a more broad spectrum of industries and job functions. The school had a decent career website and recruiting process.

The career services I thought were done fairly well, but not outstanding. Tim Weithers did a great job, as did the others.

I and many others found pretty good jobs. A combination of the right fit for a position, a little luck and networking really does a lot.

Of course, that doesn't mean everybody had the same experience I did. I also know some people who had trouble finding a job and either had to revert back to their original job function or had to look for an extended period of time. I'm not sure that's the school's or the program's fault. A bad job market and perhaps lack of planning could've contributed.

Student body
Even though the network was smaller, I met and keep in touch with quite a few people from the program. I have many fond memories of U of C and the program and did a lot of learning there. No amount of disparaging remarks about the program, the professors or the students will change that.

I mentioned the class size above, which made it harder to meet more good people. Again, I believe this has changed and thank God for that.
Master's degree in computer science. Worked for a bank as a risk analyst and currently working as an energy trading strategist for a major energy company. I am located in Singapore and report to boss in UK.
I studied part-time in the Chicago MSMF Singapore program since Sept 2009

Did you get admitted to other programs?

Why did you choose this program (over others, if applicable)?
I only applied for UChicago MSFM Singapore as it seems the best choice in Singapore or even Asia in terms of reputation.

Application process
The website was and is outdated. Most of the information regarding this program was found in online discussions. They responded my emails selectively.

Courses selection
1. Course selection is not flexible. I like Statistical Risk Management, Mathematical Foundation Option Pricing and Fixed Income so far.
2. Singapore students can study in Chicago for 1 or 2 quarters our of 3 quarters. a lot of us chose to go to Chicago in Spring quarter Apr - Jun
3. We can choose one course from Chicago Booth, which is only available in Chicago campus

Quality of teaching
1. Practitioners teaching Fixed Income are good. because the course is reduced for some reason they insist offering additional seminar which is not counted in grading.

2. the class is like a video-conference bringing people from Chicago, Singapore and Stamford together. the video quality is good. we can ask questions using a microphone. all classes are recorded and can be played back later.

3. Teachers for each course normally come to teach in Singapore for 2 weeks, giving lectures and office hours.

4. Singapore program has local TAs for every course, mostly previous graduates. They are very helpful. Without TA's help it's not possible to figure out homework. In terms of homework, TAs are much more useful than lecturers.

Materials used in the program
Notes are enough

Programming component of the program
Matlab is dominant. There's C# class but i haven't taken. For me not much programming except the Matlab programming in statistical risk management and regression analysis.

so far i haven't done any project, expecting one for Regression Analysis.

Career service
1. We visited a couple of banks in Singapore
2. Our resumes are compiled and sent to banks
3. Other than campus recruitment, quite a few immediate openings have been sourced by local career service.
4. nothing specific to intern

Student body
Ethnics are quite diversified and balanced. we are also invited to Chicago Booth alumni gathering in Singapore.

What do you like about the program?
I am much more confident about my math now. previously i picked up some models on my own, which can't compare to what I learn in the program in terms of both coverage and depth.

What DON'T you like about the program?
1. the most important course Stochastic Calculus should be taught much better.
2. the management doesn't care much about publicity. i think for a professional program this is very important. the more people appreciate the program the more value that the current students and previous graduates get.

Suggestions for the program to make it better
I would hire a public relationship manager to advertise the program better.

What are your current job status? What are you looking for?
as a quant strategist in energy trading. i want to expand my skill set further and look for more challenging opportunities, e.g. trading, portfolio manager, deal originator, etc

Bachelor degress in Math and Statistics in the US. Worked as a investment analyst before going to UChicago MSFM program. Currently working as a quantitative trader in Chicago.

Did you get admitted to other programs?

Why did you choose this program (over others, if applicable)?
It is the location. Chicago is the hub of trading business. I decided to come to Chicago to start my career in trading.

Application process
The application process is pretty easy. Submit the transcripts , resumes, application statements with a video.

Courses selection

Recently UChicago has been working hard on improving the courses. Right now in the first quarter, it offers a Python class which requires zero background in coding and the class will eventually cover a pretty decent depth in the topic of programming. E.g Inheriance, OOP, Concurrency, TCP servers.

There are a lot of trading related classes which I liked the most. Quantitative trading, applied algo trading and Machine Learning in Finance.

The new Machine learning in fiance is also a great class as to get into the application respective of machine learning in finance and trading. However, the class is not easy and requires a lot of work to understand the Mathematics concepts behind each algorithm.

The option pricing classes are the core classes at UChicago MSMF program. Professor Roger Lee always has a great way of getting you to understand the hard Math concepts.

There are still some required classes which involve heavy math. e.g Stocastic calculus , Fixed income derivates.
Making them as elective classes would be a better choise.

Quality of teaching

Option class are always on the top of the academia. Professor Lee always has his unique way of expressing complicated option concept into plain English. I enjoyed both his classes despite the heavy math concepts behind.

There are many trading professionals lecturing the classes. E.g Quantitative trading and regression classes are great class to get started in trading. I was asked a lot during the interview processes.

I really appreciated the video recording of the lectures. I can review any class again.

Materials used in the program
Notes are enough

Programming component of the program

They are teaching C++ and Python from zero.
Matlab is needed for a lot of classes, you can use Python or R for most of these classes as well
I picked up C++ and Python from almost zero and know using them for daily work.

Lots of interesting projects. Very time consuming but you can learn a lot from it

Career service

Location, location, location. Chicago has a lot of trading firms and exchanges.
Career service provides mock interviews and organizing recruiting events.
However, it is still a lot of work for the students to prepare.

What do you like about the program?
A lot of interesting classes, events and workshops. It prepares me for starting a career in trading industry.
The professors and lecturers are easy to work with.
You can learn programming efficiently and masters it during the program.

The project lab is a great way of getting working experience while still in school. It helps a lot on the resume building as well.

What DON'T you like about the program?
Some of the classes are still pretty theoretical, need to be more pratical
First quarter is very intensive, while we need to prepare for the interviews.

Suggestions for the program to make it better

Consider to drop some of the heavy math classes, add in more practical classes.

What are your current job status? What are you looking for?
I'm currently working as a quantitative trader. I'm planning to become a quantitative portoflio manager soon.
A year out from graduating here, I wanted to give a fair evaluation of the Financial Mathematics Program at the University of Chicago (U of C). The program has its problems, but I gave 5 stars ultimately because my high expectations were met

Came from Australia. Bachelor of Actuarial Studies / Bachelor of Finance. 2 years work experience at an actuarial consultancy, 2 internships at banks in market risk and credit risk. Qualified actuary

Did you get admitted to other programs?
Yes. My next choice would have been Columbia MSOR

Why did you choose this program (over others, if applicable)?
- I was dead set on becoming a trader and Chicago is the trading hub of the world. There are so many trading firms in Chicago, as well as elite hedge funds. The banks mainly operate out of New York

- U of C has a competitive advantage for the job market in Chicago. This is HUGE. There are only two nearby schools I can think of that compete; the University of Illinois and Northwestern. U of I is still annoyingly far away, and as far as I know Northwestern doesn't have a relevant masters program

- Massive brand name. The ranking system that people seem to care about most over here is the USNews one, where U of C is right up there. You'll get interviews in any city. Companies love this school in general

- The actual beauty of the school. Whether it's the amazing libraries, lecture theaters where countless nobel laureates have taught, or the actual MSFM building/house, the school itself is absolutely inspiring. I have to admit, I didn't know U of C was a top school before starting to research graduate programs, but there's no doubt in my mind that it's one of finest academic institutions in the world

- Project Lab (mentioned below)

- The business school. Even though the masters degree is separate, it doesn't hurt to have one of the top business schools on campus. You can try to take courses there (with extra approval). I worked on research in Booth, which was great

- Chicago is beautiful

- The courses are taught by heavyweights in both academics and practice

Application process
Standard process apart from an extra video that you have to provide, answering a couple questions

Course selection
Good range of courses taught on a quarter system (VERY intense). Here are some key points:

- Courses are at night to accommodate for lecturers who work outside of U of C
- One month of refresh courses before the program actually starts. This is a great time to get ready and even start putting in internship applications
- Decent range of electives, including ones on trading directly, machine learning, and time series analysis (taught in Booth). Generally speaking, the core courses are very theoretical and electives are practical
- The options courses are fantastic
- Increasing focus on computer programming. I believe the main language used has been switched to python
- Some very technical mathematics, including stats and calculus courses. These weren't too useful to me, as I wasn't pursuing a pure quant path and had already learned a lot of the material as an undergrad. They were also taught at lightning speed
- Courses on portfolio theory are good. I'm not sure if this is still the case, but both were compulsory; one was on credit risk, which I didn't find useful at all for my career path
- You can test out of some of the programming and an introductory finance course. The introductory finance course I heard was a waste of money

Quality of teaching
Some amazing lecturers and some not-so-amazing lecturers. As I mentioned, there are both academics and practitioners. Being a top school, the academics are very knowledgeable. Being a trading hub, the practitioners are also very knowledgeable (some are current or ex-head quants at top-tier firms). My favourites (in no order) were: Brian Boonstra, Mark Hendricks, Yuri Balasanov, Niels Nygaard, Roger Lee and Chanaka Liyanaarachi

Materials used in the program
A computer and a brain

Notably there is Project Lab, which is a cooperative project between a group of students and a company. This is the MSFM program's trump card. I'm not completely sure on the statistic, but something like 100% of students who apply for Project Lab will end up on a project. The companies are: trading firms (IMC, Belvedere, etc.), hedge funds/asset managers, exchanges and consultancies. I don't believe any banks are in the rotation

Career service
I never really used the MSFM career service apart from our job board, because hustle generally works. Our job board is good. Honestly the careers office seemed a bit small for the number of students and money being hauled in from tuition. This has been restructured since I left though. Outside of the program, there are big career fairs at U of C, as well as companies pencilled in weekly for presentations; these are amazing.

Student body
Very smart students with not a lot of work experience. Not demographically diverse enough in my year; 95% foreign students from Asia. Cheating is treated harshly, which I think is the right way to go. It's an EXTREMELY intense program though, so many resort to cheating. There are a handful of professionals taking the course part time after work

What do you like about the program?
To sum it up, I entered the Financial Mathematics Program at the University of Chicago to learn, AND THEN from that find a job. That's exactly what happened; I learned a boat load, both through the program and on my own... and out of it have come some fruitful years in the US

Suggestions for the program to make it better
- Shave away some of the worse courses or make them electives
- Try to become more diverse without sacrificing student quality
- Beef up the careers services
- Create alumni events in New York ;)

What is your current job status?
Quantitative options trader at a midsize market making firm

Bachelor's degree in Engineering from India. Worked as a sell-side analyst for 2 years before going to UChicago MSFM program. Currently working as a desk quant in a bulge bracket.

Did you get admitted to other programs?
Yes, Georgia Tech QCF, Columbia MAFN

Why did you choose this program (over others, if applicable)?
Because of the location, brand- name and some scholarship.

Application process
The application process is pretty easy. Submit the transcripts, resumes, application statements with a video.

Courses selection
The courses which liked the most were Options Pricing, Numerical Methods, and Portfolio Theory. Python has become the primary language of the program. Right from September review students are taught Python programming (which I don't see in other MFE programs). I found this to be very helpful in the internship/job interviews. Other programming courses include C++ programming and advanced C++ programming applications.

During the September review, there were some technical interview preparation workshops which I really liked.

There are trading related classes such as Quantitative trading, Applied Algo trading, and Machine Learning in Finance.

Machine learning in finance is a good class to get into the application respective of machine learning in finance and trading. However, this class can be improved a lot.

There are still some required and elective classes that involve heavy math. e.g Stochastic calculus, Fixed income derivates.

Quality of teaching

Option classes are always at the top of academia. Professor Roger Lee always has a unique way of expressing complicated option concepts in simple terms. I enjoyed both his classes despite the heavy math concepts behind.

Prof Mark Hendricks Portfolio Theory is very practical, he follows a business school teaching style where his assignments are interesting case studies by asset management companies.
There are many trading professionals lecturing the classes. E.g Quantitative trading and regression classes are great to get started in trading.
The Machine Learning and Deep Learning classes still need some improvements though.

I really appreciated the video recording of the lectures. I can review any class again.

Overall, the teaching quality is good except for one or two courses. The faculty is a blend of academic professors and industry practitioners

Overall the curriculum is good but needs more elective courses.

Project Lab
This a collaboration between Uchicago Finmath students and companies (hedge funds, banks, asset managers) to work on some real-world research projects. This is the MSFM program's trump card. I know some students (2 or 3 ) who got their internships and full-time roles through project labs but still, it's difficult to convert. But this is really important for those students who come with no prior experience as they can work on lots of interesting projects. Very time consuming but you can learn a lot from it.

Career service
According to my understanding, the career service has improved greatly in the past 3 years. I attended many networking events, company information sessions, interview workshops, recruiting events and alumni panels. The Career Development Office helps you a lot in interview preparation. The program is making its best efforts to forge good relationships with employers.

Chicago has a lot of trading firms and exchanges. So it's the ideal place for students trying to get into trading shops. New York anytime is the better location as compared to Chicago. U of C has a competitive advantage for the job market in Chicago. Firms based out of Chicago like interviewing students from this school.

What DON'T you like about the program?
Some of the classes are still pretty theoretical, need to be more practical. Machine Learning course needs improvement.

Suggestions for the program to make it better :

Consider improving Machine Learning and Deep Learning class. Add more electives.

What is your current job status?
I will be working as a desk quant in a bulge bracket.
I recently graduated from the FinMath program in Dec 2019.
Overall Experience:
I was very satisfied with the teaching, career services, and professional opportunities provided. The program is majorly taught in Python, and a few classes are in C++.

Things that can be improved: The program can improve on adding more electives, and improve some of the existing ones (namely Machine Learning). Maybe we can have some more advanced classes being offered as electives outside FINM.

Courses: Stand out courses are Option Pricing, Portfolio theory, Quant Strategies. Another advantage is some of the electives offered are cross-listed with the Business school, or Statistics departments, so you can fine tune the course to your requirement.

Project Lab: One of the best experiences to work with companies (HF,AM,Banks) on real problem that they want explore and solve.

Career Services: We had plenty of networking events, company events and alumni dinners to network. I believe the career office is doing a fairly good job.
  • Anonymous
  • 5.00 star(s)
To echo some of the other sentiment on this forum -- there are certainly minor issues that need to be addressed, but ultimately the program as a whole is fundamentally solid. The curriculum is put together cohesively, and for the most part, the quality of teaching is superb. Faculty and staff are all incredibly friendly and caring -- in particular, the student services administrator, Meredith, is great. The program is admittedly pretty difficult. I came from a Math background and sometimes still had trouble on problem sets. Coding in Python is emphasized throughout most courses.

I'll skip all the small details and focus on the most important things: relevance of coursework, quality of teaching, and career advancement services.

Relevance of Coursework:
I think Roger (the director of the program) works really hard to construct a curriculum that follows a rational progression, and overall I agree with most of his choices. The best courses are Portfolio Theory, Options Pricing, and Numerical Methods. Project Lab, a course that allows you to work with outside companies, is an added plus because it gives you exposure with real-world problems. You can also take courses from Booth or the Statistics department -- these are really good.

Having an intermediate-level Probability and Statistics course during the first quarter would be godsend for recruiting; I know there is one in place right now, but it focuses too much on theory.

Quality of Teaching:
For the most part, the quality is pretty good, but there are definitely some courses that could be taught better (I think the program is fully aware of which ones). Roger Lee and Mark Hendricks are fantastic. Sebastien Donadio (the instructor for Python) is pretty good, although I would argue that while you learn a lot of Python in his class, you do it inefficiently. From my personal experiences, I think there are more efficient ways to teach coding than to bombard students with a heavy amount of coding assignments (some useful, some not). I'm not sure if this has changed since I graduated. But if you want to learn a lot, Seb is your guy.

Career Services:
If you want to do trading, the location is an added plus because Chicago has a high density of prop trading/market making firms.

The career services people are friendly and helpful, but one has to realize there's only so much they can do. They do a good job of putting together and coordinating workshops, and try to provide as many resources and references as they can, but it ultimately depends on the students to actually prepare for recruiting. Recruiting is more a matter of diligence and mental fortitude than anything else, so job placement ultimately depends on the individual more than anything else. New students shouldn't expect to walk into the program and assume that they have a job locked up after graduation, but if you put in the effort you should be fine.